UCF-Crime is a large-scale dataset of real-world surveillance videos, including 13 types of anomalous events with 1900 long untrimmed videos, where 1610 videos are training videos and the others are test videos. Liu et al. [1]} manually annotated bounding boxes of anomalous regions in one image per 16 frames for each abnormal video, and we use their annotation of test videos only to evaluate our model's capacity to identify anomalous regions.
